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RichardErkhov/
clinno_-_eightwords-20241112-gguf

Name: clinno_-_eightwords-20241112-gguf
Availability: InStock

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eightwords-20241112 - GGUF

Model creator: https://huggingface.co/clinno/
Original model: https://huggingface.co/clinno/eightwords-20241112/

Name	Quant method	Size
eightwords-20241112.Q2_K.gguf	Q2_K	2.96GB
eightwords-20241112.IQ3_XS.gguf	IQ3_XS	3.28GB
eightwords-20241112.IQ3_S.gguf	IQ3_S	3.43GB
eightwords-20241112.Q3_K_S.gguf	Q3_K_S	3.41GB
eightwords-20241112.IQ3_M.gguf	IQ3_M	3.52GB
eightwords-20241112.Q3_K.gguf	Q3_K	3.74GB
eightwords-20241112.Q3_K_M.gguf	Q3_K_M	3.74GB
eightwords-20241112.Q3_K_L.gguf	Q3_K_L	4.03GB
eightwords-20241112.IQ4_XS.gguf	IQ4_XS	4.18GB
eightwords-20241112.Q4_0.gguf	Q4_0	4.34GB
eightwords-20241112.IQ4_NL.gguf	IQ4_NL	4.38GB
eightwords-20241112.Q4_K_S.gguf	Q4_K_S	4.37GB
eightwords-20241112.Q4_K.gguf	Q4_K	4.58GB
eightwords-20241112.Q4_K_M.gguf	Q4_K_M	4.58GB
eightwords-20241112.Q4_1.gguf	Q4_1	4.78GB
eightwords-20241112.Q5_0.gguf	Q5_0	5.21GB
eightwords-20241112.Q5_K_S.gguf	Q5_K_S	5.21GB
eightwords-20241112.Q5_K.gguf	Q5_K	5.34GB
eightwords-20241112.Q5_K_M.gguf	Q5_K_M	5.34GB
eightwords-20241112.Q5_1.gguf	Q5_1	5.65GB
eightwords-20241112.Q6_K.gguf	Q6_K	6.14GB
eightwords-20241112.Q8_0.gguf	Q8_0	7.95GB

Original model description:

library_name: transformers license: other base_model: NousResearch/Meta-Llama-3-8B-Instruct tags:

llama-factory
full
generated_from_trainer model-index:
name: sft results: []

sft

This model is a fine-tuned version of NousResearch/Meta-Llama-3-8B-Instruct on the identity and the eightwords-20241112-alapaca datasets. It achieves the following results on the evaluation set:

Loss: 1.6951

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 1e-05
train_batch_size: 2
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 32.0

Training results

Training Loss	Epoch	Step	Validation Loss
0.7669	14.0474	2000	1.4163
0.4249	28.0948	4000	1.6929

Framework versions

Transformers 4.44.2
Pytorch 2.5.0+cu121
Datasets 3.1.0
Tokenizers 0.19.1

RichardErkhov/clinno_-_eightwords-20241112-gguf

Original model description:

sft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

RichardErkhov/
clinno_-_eightwords-20241112-gguf